Data Analyst

FORTUNIZE INDIA TECHNOLOGY SOLUTIONS PRIVATE LIMITED; Hyderabad; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Fortunize India Technology Solutions Private Limited is seeking a Data Analyst to enable data-informed decision‑making across our commercial vertical. You will develop, maintain, and optimize data, reporting tools and dashboards that support loan origination, underwriting, and portfolio management.

The ideal candidate is detail‑oriented, technically proficient, and highly collaborative, with 3+ years of experience in data analysis and strong SQL skills.

Qualifications

• Bachelor’s degree in a quantitative field.
• 3+ years of relevant experience in data analysis or business intelligence, ideally in fintech, financial services, or lending.
• Strong SQL skills and experience working with relational databases.
• Proficiency with data visualization tools (e.g., Tableau, Power BI, Looker, or similar).
• Excellent attention to detail and commitment to data accuracy.
• Strong communication skills, with the ability to explain technical findings to non‑technical audiences.

Responsibilities

• Design, build, and maintain operational dashboards and recurring reports to track KPIs related to loan volume, processing times, approval rates, and servicing metrics.
• Collaborate with operations, credit risk, underwriting, product, and finance teams to identify reporting needs and translate business requirements into efficient data queries and visualizations.
• Ensure data accuracy and integrity across operational reports, proactively identifying and resolving discrepancies or anomalies.
• Analyze trends in application flow, merchant behavior, and advance performance to inform process improvements and resource planning.
• Develop documentation and maintain data dictionaries to support data governance and stakeholder self‑service.
• Support ad hoc reporting requests and contribute to cross‑functional data initiatives

Skills

SQL

Data Visualization

Python

R

Communication

Education

Bachelor’s degree in a quantitative field

Tools

Tableau

Power BI

Looker

Relational Databases

Job description

The Data Analyst, will play a key role in enabling data-informed decision‑making across our commercial vertical. This position is responsible for developing, maintaining, and optimizing data, reporting tools and dashboards that support loan origination, underwriting, and portfolio management. The ideal candidate is detail‑oriented, technically proficient, and highly collaborative.

What will you do:

• Design, build, and maintain operational dashboards and recurring reports to track key performance indicators (KPIs) related to loan volume, processing times, approval rates, and servicing metrics.
• Collaborate with operations, credit risk, underwriting, product, and finance teams to identify reporting needs and translate business requirements into efficient data queries and visualizations.
• Ensure data accuracy and integrity across operational reports, proactively identifying and resolving discrepancies or anomalies.
• Analyze trends in application flow, merchant behavior, and advance performance to inform process improvements and resource planning.
• Develop documentation and maintain data dictionaries to support data governance and stakeholder self‑service.
• Support ad hoc reporting requests and contribute to cross‑functional data initiatives

What are we looking for:

• Bachelor’s degree in a quantitative field (e.g., Statistics, Business Analytics, Economics, Computer Science, or related discipline).
• 3+ years of relevant experience in data analysis or business intelligence, ideally in fintech, financial services, or lending
• Strong SQL skills and experience working with relational databases.
• Proficiency with data visualization tools (e.g., Tableau, Power BI, Looker, or similar).
• Excellent attention to detail and commitment to data accuracy.
• Strong communication skills, with the ability to explain technical findings to non‑technical audiences.

Must Have:

• Familiarity with small business lending workflows and key operational metrics.
• Experience with Python or R for data manipulation and analysis.
• Understanding of data governance, KPI definition, and dashboard usability best practices.
• Exposure to cloud‑based data environments (e.g., Snowflake, Redshift).